• Steel and Composite Structures
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• v.29 no.6
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• pp.703-716
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• 2018

Rapid detection of damages in civil engineering structures, in order to assess their possible disorders and as a result produce competent decision making, are crucial to ensure their health and ultimately enhance the level of public safety. In traditional intelligent health monitoring methods, the features are manually extracted depending on prior knowledge and diagnostic expertise. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed here for intelligent health monitoring of civil engineering structures. In the first stage, $Nystr{\ddot{o}}m$ method is used for automatic feature extraction from structural vibration signals. In the second stage, Moving Kernel Principal Component Analysis (MKPCA) is employed to classify the health conditions based on the extracted features. In this paper, KPCA has been implemented in a new form as Moving KPCA for effectively segmenting large data and for determining the changes, as data are continuously collected. Numerical results revealed that the proposed health monitoring system has a satisfactory performance for detecting the damage scenarios of a three-story frame aluminum structure. Furthermore, the enhanced version of KPCA methods exhibited a significant improvement in sensitivity, accuracy, and effectiveness over conventional methods.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Progress in Superconductivity and Cryogenics
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• v.12 no.3
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• pp.44-48
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• 2010

Acoustic emission (AE) signal from an HTS tape has a low signal to noise ratio, due to the large amount of noise caused by the boiling of the liquid cryogen or mechanical vibration from the cryo-cooler. In an attempt to improve the sensitivity of the AE sensor, $Pb(Zr_{0.54}Ti_{0.46})O_3$ + 0.2 wt% $Cr_2O_3$ + 1.0 wt.% $Nb_2O_5$ ceramics sintered at $1200^{\circ}C$ was synthesized. In addition, the resonance ($f_r$) and anti-resonance frequencies ($f_a$) were measured using the specimens with various thicknesses (1.0, 1.5, 2.0, 2.5 and 3.0 mm). According to the test results, large AE signals with high frequencies were obtained from the AE sensor fabricated using a piezoelectric disc with a thinner thickness.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.199-206
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• 2023

This study presents a novel monitoring technique for underwater high-voltage direct current (HVDC) cables based on the Distributed Acoustic Sensor (DAS). The proposed technique utilizes vibration and acoustic signals generated on HVDC cables to monitor their condition and detect events such as earthquakes, shipments, tidal currents, and construction activities. To implement the monitoring system, a DAS based on phase-sensitive optical time-domain reflectometry (Φ-OTDR) system was designed, fabricated, and validated for performance. For the HVDC cable monitoring experiments, a testbed was constructed on land, mimicking the cable burial method and protective equipment used underwater. Defined various scenarios that could cause cable damage and conducted experiments accordingly. The developed DAS system achieved a maximum measurement distance of 50 km, a distance measurement interval of 2 m, and a measurement repetition rate of 1 kHz. Extensive experiments conducted on HVDC cables and protective facilities demonstrated the practical potential of the DAS system for monitoring underwater and underground areas.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.459-466
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• 2011

Sleep diseases such as snoring and sleep apnea are physically, mentally harmful and results serious health problems. Snoring, known as breathing noise, is caused by coupled oscillation of the airway when the air passes through the trachea, and sleep apnea is caused by upper airway blockage. In order to solve these problems, many attempts have been made to detect the snoring during sleep and alleviate it. In this study, a new sensing system and analysis algorithm were developed in order to detect snoring sounds correctly under various sleep environments. Two polyvinylidene fluoride (PVDF) vibration sensors were used inside the pillow. The first PVDF sensor detects vibration transmitted through skull caused by snoring. And the second PVDF sensor detects both snoring sounds and ambient noises. The signals of two sensors were acquired through the designed analog circuits, and analyzed for snoring detection. Ten volunteers were participated for the experiment under five different conditions. Data from two PVDF sensors were processed by the established analysis algorithm, and snoring sounds were compared to noises. The results indicated that the energy of snoring is 70% bigger than that of ambient noise, which proves effectiveness of sensing system and analysis algorithm. Further study would be continued for more wide clinical studies with various environment noises. Based on this study, development of anti-snore pillow and sleep monitoring system for comfort sleep could be developed.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.195-202
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• 2016

There have been many studies on subject tests for 3D contents using 3D glasses, but there is a limited research for 3D contents using autostereoscopic display. In this study, we investigated to assess usability of electroencephalogram (EEG) as an objective evaluation for 3D contents with different quality using autosteroscopic display, especially for lenticular lens type. The image with optimal quality and the image with distorted quality were separately generated for autostereosopic display with lenticular lens type and displayed sequentially through lenticular lens for 26 subjects. EEG signals of 8 channels from 26 subjects exposed to those images were detected and correlation between EEG signal and the quality of 3D images were statistically evaluated to check differences between optimal and distorted 3D contents. What we found was that there was no statistical significance for a wave vibration, however b wave vibration shows statistically significant between optimal and distorted 3D contents. b wave vibration observed for the distorted 3D image was stronger than that for the optimal 3D image. This results suggest that subjects viewing the distorted 3D contents through lenticular lens experience more discomfort or fatigue than those for the optimum 3D contents, which resulting in the greater b wave activity for those watching the distorted 3D contents. In conclusion, these results confirm that electroencephalogram (EEG) analysis can be used as a tool for objective evaluation of 3D contents using autosteroscopic display with lenticular lens type.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.5
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• pp.92-100
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• 2011

This paper describes a numerical modeling for deflection calculation using the natural frequency response that is measured acceleration response for concrete bridges. In the formulation of the dynamic deflection, the change amounts and the transformed responses about six kinds of free vibration responses are defined totally. The predicted response can be obtained from the measured acceleration data without requiring the knowledge of the initial velocity and displacement information. The relationship between the predicted response and the actual deflection is derived using the mathematical modeling that is induced by the process of a acceleration test data. In this study, in order to apply the proposed response predicted model to the integration scheme of the natural frequency domain, the Fourier Fast Transform of the deflection response is separated into the frequency component of the measured data. The feasibility for field application of the proposed calculation method is tested by the mode superposition method using the PSC-I bridges superstructures under several cases of moving load and results are compared with the actually measured deflections using transducers. It has been observed that the proposed method can asses the deflection responses successfully when the measured acceleration signals include the vehicle loading state and the free vibration behavior.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.5-13
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• 2015

For the bearing capacity evaluation, dynamic pile tests instead of static pile tests have been commonly used in embedded piles, which are known to have low noise and low vibration construction method. The objective of this study is to analyze the bearing capacity and penetration behaviors of embedded piles, which are constructed in different ground conditions, by using force and velocity signals obtained in the final blows during construction of embedded piles. For the dynamic pile analyses, the CAse Pile Wave Analysis Program (CAPWAP) and Wave Equation Analysis of Piles (WEAP) have been commonly used. In this study, the CAPWAP and WEAP are used for the analyses of the dynamic pile tests, which are conducted on embedded piles. The input values, output values, and force-velocity graphs of CAPWAP determined by analyzing the measured force-velocity signals are investigated. In addition, similar force-velocity singals are obtained from the WEAP by analyzing the input values of the WEAP. Considering the subsurface investigation results around the pile tips, if the N-value increases exponentially along the depth, toe quake value should be small, and therefore large bearing capacity is identified. On the contrary, if the N-value increases linearly, the bearing capacity is small because of large toe quake value. Furthermore, the stiffness of hammer cushion and pile cushion, which is difficult to find correct values, is recommended lower than 500 kN/mm. This study demonstrates that the results of WEAP may be similar to those of CAPWAP and the WEAP can be used to estimate the bearing capacity of embedded piles.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.3
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• pp.11-19
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• 2009

Recently, concerns relating to the maintenance of large structures have been increased. In addition, the number of large structures that need to be evaluated for their structural safety due to natural disasters and structural deterioration has been rapidly increasing. It is common for the structural characteristics of an older large structure to differ from the characteristics in the initial design stage, and changes in dynamic characteristics may result from a reduction in stiffness due to cracks on the materials. The process of deterioration of such structures enables the detection of damaged locations, as well as a quantitative evaluation. One of the typical measuring instruments used for the monitoring of bridges and buildings is the dynamic measurement system. Conventional dynamic measurement systems require considerable cabling to facilitate a direct connection between sensor and DAQ logger. For this reason, a method of measuring structural responses from a remote distance without the mounted sensors is needed. In terms of non-contact methods that are applicable to dynamic response measurement, the methods using the doppler effect of a laser or a GPS are commonly used. However, such methods could not be generally applied to bridge structures because of their costs and inaccuracies. Alternatively, a method using a visual image can be economical as well as feasible for measuring vibration signals of inaccessible bridge structures and extracting their dynamic characteristics. Many studies have been conducted using camera visual signals instead of conventional mounted sensors. However, these studies have been focused on measuring displacement response by an image processing technique after recording a position of the target mounted on the structure, in which the number of measurement targets may be limited. Therefore, in this study, a model experiment was carried out to verify the measurement algorithm for measuring multi-point displacement responses by using a DIC (Digital Image Correlation) technique.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.9 no.5
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• pp.447-453
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• 1999

Congruent $LiNbO_3$ crystals with doped Mg and codoped with Mn or Fe were grown by the Czochralski method. It is known that the physical properties of $LiNbO_3$ depend strongly on the addition of Mg and transition metals. This is established by studying the following properties; XRD patterns, the phase transition temperature, energy of the fundamental absorption edge, the shape of the absorption band of the $OH^-$ vibration and lines of the ESR of $Fe^{3+},\; Mn^{2+}$. The position of the UV absorption edge and the shape and peak point of the absorption band of the $OH^-$ vibrational band changed monotonously up to a critical concentration of $Mg^{2+}$ ions. The mechanism of the incorporation of Mg ions changes at this concentration. The transition temperature was estimated by measuring the dielectric temperature behavior up to $1230^{\circ}C$ in a frequency range of 100Hz to 10MHz. EPR of $Mn^{2+}\;and\; Fe^{3+}$ ions were employed to investigated the Mg doping effects in the $LiNbO_3$ crystal. The increase of linewidths and the asymmetry of signals were observed in all crystals. New signals of $Fe^{3+}$ arising from the new centers were observed I the heavily Mg-doped crystals.